{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Main.DCGAN"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using Knet\n",
    "include(\"dcgan.jl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = DCGAN.sample_noise(KnetArray{Float32},100,64);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training started...\n"
     ]
    }
   ],
   "source": [
    "wd, wg, md, mg = DCGAN.main(\"--epochs 0 --seed 1\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "233×233 reinterpret(Gray{Float64}, ::Array{Float64,2}):\n",
       " Gray{Float64}(1.0)  Gray{Float64}(1.0)       Gray{Float64}(1.0)       …  Gray{Float64}(1.0)       Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502222)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502222)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)  …  Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502222)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502222)     Gray{Float64}(0.502222)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502222)  …  Gray{Float64}(0.502222)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502222)  Gray{Float64}(0.502222)     Gray{Float64}(0.502222)  Gray{Float64}(1.0)\n",
       " ⋮                                                                     ⋱                           \n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502222)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502222)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502222)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502222)  …  Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502222)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502222)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502222)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)  …  Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.502221)  Gray{Float64}(0.502221)     Gray{Float64}(0.502221)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(1.0)       Gray{Float64}(1.0)          Gray{Float64}(1.0)       Gray{Float64}(1.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "DCGAN.plot_generations(wg, mg; z=z);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training started...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:35/00:35, 17.36i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 1, :dloss, 0.84712666f0, :gloss, 1.2757794f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 54.38i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 2, :dloss, 0.7991464f0, :gloss, 1.4329474f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 55.84i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 3, :dloss, 0.85160375f0, :gloss, 1.374077f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 55.66i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 4, :dloss, 0.8214035f0, :gloss, 1.4378794f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 54.98i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 5, :dloss, 0.79875445f0, :gloss, 1.4880217f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 54.87i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 6, :dloss, 0.7830885f0, :gloss, 1.5254846f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 53.17i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 7, :dloss, 0.7588902f0, :gloss, 1.5633898f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 55.31i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 8, :dloss, 0.7438721f0, :gloss, 1.6127883f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 53.42i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 9, :dloss, 0.72154135f0, :gloss, 1.6764766f0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┣████████████████████┫ [100.00%, 600/600, 00:11/00:11, 54.42i/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(:epoch, 10, :dloss, 0.70294815f0, :gloss, 1.7254875f0)\n"
     ]
    }
   ],
   "source": [
    "wd, wg, md, mg = DCGAN.main(\"--epochs 10 --seed 1\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "233×233 reinterpret(Gray{Float64}, ::Array{Float64,2}):\n",
       " Gray{Float64}(1.0)  Gray{Float64}(1.0)         Gray{Float64}(1.0)          …  Gray{Float64}(1.0)          Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.110921)    Gray{Float64}(0.0600011)       Gray{Float64}(0.105835)     Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0589436)   Gray{Float64}(0.0124256)       Gray{Float64}(0.0304795)    Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0151955)   Gray{Float64}(0.0030216)       Gray{Float64}(0.0107774)    Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0120051)   Gray{Float64}(0.00382745)      Gray{Float64}(0.00928912)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00506595)  Gray{Float64}(0.000931203)  …  Gray{Float64}(0.00305831)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00677243)  Gray{Float64}(0.000589162)     Gray{Float64}(0.00168595)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00298226)  Gray{Float64}(0.000493735)     Gray{Float64}(0.00107896)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00382707)  Gray{Float64}(0.00036487)      Gray{Float64}(0.00155389)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0026136)   Gray{Float64}(0.000144213)     Gray{Float64}(0.00206372)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00443944)  Gray{Float64}(0.000246733)  …  Gray{Float64}(0.00116792)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00456896)  Gray{Float64}(0.000403643)     Gray{Float64}(0.000259548)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0071573)   Gray{Float64}(0.000530899)     Gray{Float64}(0.000198156)  Gray{Float64}(1.0)\n",
       " ⋮                                                                          ⋱                              \n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00301215)  Gray{Float64}(0.000146419)     Gray{Float64}(0.00887951)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00330466)  Gray{Float64}(0.000127435)     Gray{Float64}(0.0112918)    Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00538364)  Gray{Float64}(0.000229239)     Gray{Float64}(0.0131411)    Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00444984)  Gray{Float64}(0.000163943)     Gray{Float64}(0.00851318)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00607625)  Gray{Float64}(0.000321388)  …  Gray{Float64}(0.00398403)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0057869)   Gray{Float64}(0.000476778)     Gray{Float64}(0.0013954)    Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0061709)   Gray{Float64}(0.00039655)      Gray{Float64}(0.000637114)  Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.00825152)  Gray{Float64}(0.000499696)     Gray{Float64}(0.00103983)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0152274)   Gray{Float64}(0.00139588)      Gray{Float64}(0.00459054)   Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0285893)   Gray{Float64}(0.00420454)   …  Gray{Float64}(0.0338144)    Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(0.0707422)   Gray{Float64}(0.0160548)       Gray{Float64}(0.109667)     Gray{Float64}(1.0)\n",
       " Gray{Float64}(1.0)  Gray{Float64}(1.0)         Gray{Float64}(1.0)             Gray{Float64}(1.0)          Gray{Float64}(1.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "DCGAN.plot_generations(wg, mg; z=z)"
   ]
  }
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